{"id":853,"date":"2016-01-27T09:35:47","date_gmt":"2016-01-27T17:35:47","guid":{"rendered":"https:\/\/www.genrocket.com\/?p=853"},"modified":"2022-09-05T16:41:49","modified_gmt":"2022-09-05T16:41:49","slug":"better-software-testing-with-conditioned-test-data","status":"publish","type":"post","link":"https:\/\/www.genrocket.com\/blog\/better-software-testing-with-conditioned-test-data\/","title":{"rendered":"Better Software Testing with Conditioned Test Data"},"content":{"rendered":"

One of the most important aspects of software testing<\/a> is being able to\u00a0condition the test data you require to fully run a\u00a0given test.<\/span><\/p>\n

Conditioned test data gives you the ability to test for a specific outcome within a given unit<\/strong>,\u00a0integration<\/strong>, load<\/strong> test or\u00a0functionally<\/strong> test a specific workflow or control the test data presented in a demo application.<\/span><\/p>\n

The MultiWeightGen Generator is one of GenRocket\u2019s best Generators for controlling the frequency (on a percentage basis) of how one or more values are generated within a finite set of generated test data.<\/span><\/p>\n

Let\u2019s take the following example to see the MultiWeightGen Generator in action.<\/span><\/p>\n

The Test Data Challenge<\/span><\/h2>\n

A tester needs to run an integration test to produce a very specific set of test data to assert that the business logic within a given service method is working correctly. The service method takes a code name, a set of data, and returns the percentage of time the specific code name was found within the set of data.<\/span><\/p>\n

In order to thoroughly test the business logic, the tester needs to generate a specific percentage of different code names for a finite set of data:<\/span><\/p>\n

\u00a0 <\/strong>40% of the time, generate either code Blue or code Green<\/em><\/span>
\n \u00a0 \u00a0 \u00a0Within the 40%, 80% should generate code Blue<\/em><\/span>
\n \u00a0 \u00a0 \u00a0Within the 40%, 20% should generate code Green<\/em><\/span><\/p>\n

\u00a0 60% of the time, generate either code Red or code Yellow<\/em><\/span>
\n\u00a0 \u00a0 \u00a0Within the 60%, 70% should generate code Red<\/em><\/span>
\n\u00a0 \u00a0 \u00a0Within the 60%, 30% should generate code Yellow<\/em><\/span><\/p>\n

Believe it or not, with the GenRocket MultiWeightGen Generator, this test data can be generated with only three Attributes and you can be generating the data you require in only a few minutes.<\/span><\/p>\n

Attribute\u00a0codeBlueGreen<\/span><\/h2>\n

First, create an Attribute called, codeBlueGreen, and assigned it the MultiWeightGen Generator and set Blue at 80% and Green at 20%. I also set the Attributes visible parameter to false.<\/span><\/p>\n

 <\/p>\n

\"MultiWeightGenCodeBlueGreen\"<\/a><\/span><\/p>\n

Attribute\u00a0codeRedYellow<\/span><\/h2>\n

Second, create an Attribute called, codeRedYellow, and assigned it the MultiWeightGen Generator and set Red at 70% and Yellow at 30%. I also set the Attributes visible parameter to false.<\/span><\/p>\n

 <\/p>\n

\"MultiWeightGenCodeRedYellow\"<\/a><\/span><\/p>\n

Attribute\u00a0code<\/span><\/h2>\n

Third, create an Attribute called, code, and assigned it the MultiWeightGen Generator. Then I reference Attribute codeBlueGreen at 40% and reference Attribute codeRedYellow at 60%.<\/span><\/p>\n

 <\/p>\n

\"MultiWeighGenCode\"<\/a><\/span><\/p>\n

Attribute category<\/span><\/h2>\n

So that we can query our data quickly to produce the statistics we want to review, I also added an attribute called, category, assign to it the GenRocket SwitchGen Generator and gave it the parameters as you see in the image below.<\/span><\/p>\n

 <\/p>\n

\"MultiWeighGenCategory\"<\/a><\/span><\/p>\n

Preview The Results<\/span><\/h1>\n

Click on the Domain\u2019s box icon and you can preview your results. And since Attributes codeBlueGreen and codeRedYellow have their visible parameter set to false, only Attribute\u2019s id, code and category will show visible results, which is what we want.<\/span><\/p>\n

 <\/p>\n

\"MultiWeightGenPreview\"<\/a><\/span><\/p>\n

Testing your results<\/span><\/h2>\n

Here\u2019s one cool way to see the how well the percentages turn out by populating a MySQL database table with test data and checking your results.<\/span><\/p>\n

Generate 5000 rows to an SQL file called, stats.sql.<\/span><\/h2>\n

\"MultiWeightGenSQLPreview\"<\/a><\/span><\/p>\n

Create Demo Database<\/span><\/h2>\n

Login into MySQL and run the following command to create a demo database
\n<\/span>create database demo;<\/span><\/p>\n

Create The Stats Table<\/span><\/h2>\n

DROP TABLE IF EXISTS stats;<\/span>
\nCREATE TABLE stats (<\/span>
\n\u00a0 id bigint NOT NULL AUTO_INCREMENT,<\/span>
\n\u00a0 code VARCHAR(25) NOT NULL, <\/span>
\n\u00a0 category VARCHAR(25) NOT NULL, <\/span>
\n\u00a0 PRIMARY KEY (id)<\/span>
\n) ENGINE=InnoDB;<\/span><\/p>\n

Load The Conditioned Test Data<\/span><\/h2>\n

At the command line, load the data into the table:<\/span><\/p>\n

mysql -u username -p password -D databaseName < stats.sql<\/span><\/p>\n

Run the following SQL statements<\/span><\/h1>\n

Percentage Each of Blue & Green<\/span><\/h2>\n

select code, count(code) as count, count(code)\/(<\/span>
\n select count(code) from stats where code in (‘Blue’,’Green’)<\/span>
\n) * 100 as percent <\/span>
\nfrom stats where code in (‘Blue’,’Green’) group by code;<\/span><\/p>\n

Example Output:<\/span><\/h3>\n

code count percent <\/span>
\n—- —- \u00a0——- <\/span>
\nBlue 1609 \u00a080.8949 <\/span>
\nGreen 380 \u00a019.1051<\/span><\/p>\n

\"MultiWeightGenPieBlueGreen\"<\/a><\/span><\/p>\n

Percentage Each of Red & Yellow<\/span><\/h2>\n

select code, count(code) as count, count(code)\/(<\/span>
\n select count(code) from stats where code in (‘Red’,’Yellow’)<\/span>
\n) * 100 as percent <\/span>
\nfrom stats where code in (‘Red’,’Yellow’) group by code;<\/span><\/p>\n

Example Output<\/span><\/h3>\n

code \u00a0count percent <\/span>
\n—– —– ——- <\/span>
\nRed \u00a0 \u00a02083 69.1797 <\/span>
\nYellow \u00a0928 30.8203<\/span><\/p>\n

\"MultiWeightGenPieRedYellow\"<\/a><\/span><\/p>\n

Percentage Grouped By Category<\/span><\/h2>\n

select Category, count(code)\/( select count(*) from stats)
\n<\/span>* 100 as ‘Percentage’ from stats group by Category<\/span><\/p>\n

Example Output<\/span><\/h3>\n

Category \u00a0Percentage <\/span>
\n——— ———- <\/span>
\nBlueGreen 39.7800 <\/span>
\nRedYellow 60.2200<\/span><\/p>\n

\"MultiWeightGenPieCategory\"<\/a><\/span><\/p>\n

Why are the percentages not exact?<\/span><\/h2>\n

If you\u2019re wondering why the percentages did not come out as exact percentages but close approximation instead, it\u2019s because GenRocket Generators generate their data values on each iteration; a given iteration does not know about the sum of the whole. This way the percentages are realistic and any number of rows generated can be undetermined; in essence the number or rows generated could be 100 rows or 100,000,000 rows and the percentages would still come to a very close approximation of the exact percentages.<\/span><\/p>\n

Try producing 50,000 rows and see what results you get.<\/span><\/p>\n

Why are there values set for\u00a0each\u00a0seed parameter?<\/span><\/h2>\n

If you look at the parameters set for codeBlueGreen, codeRedYellow & code, you may notice that\u00a0the seed parameter has different values. Seeding the MultiWeightGen Generator gives you greater control of your test data because it guarantees the same random data will be generated each time you generate\u00a0your test data. \u00a0This is especially beneficial if you desire a test to always yield the exact same result each time the test is run.\u00a0<\/span><\/p>\n

Checkout the MultiWeightGen In Action<\/span><\/h1>\n

To see the MultiWeightGen Generator IN ACTION; check out the video below.\u00a0<\/span><\/p>\n